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Is your feature request related to a problem? Please describe.
The Docker images are very huge and users would like to just use the base image (which doesn't contain any models). This would make it more convenient for them to work on the image and add things, without the need to upload a huge image all the time when they make changes.
Describe the solution you'd like
Specify the models they want via env variables
Make sure that private models can also be handled
Models are downloaded on first request to the worker or when the worker starts
Models are downloaded onto the network-storage. If this doesn't exist, we will not download anything, as this would totally screw up the cold start time otherwise
Describe alternatives you've considered
Use the base image
Download the models manually onto the network storage
Use the network storage with the deployed endpoint
It's been awhile, but I recall trying this via a custom image I built. And the long initial download times caused the Runpod serverless process to restart the worker repeatedly... which then tried to download the image. Perhaps that's been changed, dunno.
A simpler, and more reliable way to accomplish your goal of a smaller image: mount your network volume using a CPU-only / cheap GPU pod, download the models to it, and then use the models from this image. But keep in mind that loading models from the NAS is much slower than on-disk.
Is your feature request related to a problem? Please describe.
The Docker images are very huge and users would like to just use the
base
image (which doesn't contain any models). This would make it more convenient for them to work on the image and add things, without the need to upload a huge image all the time when they make changes.Describe the solution you'd like
Describe alternatives you've considered
base
imageAdditional context
This idea came to life because of https://discord.com/channels/912829806415085598/1273963578369642557 and https://discord.com/channels/912829806415085598/1270792081580753047.
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